Distributed Systems

1
Distributed Systems

• Sukumar Ghosh
• Department of Computer Science
• University of Iowa

2
Definition?
A distributed system is one in which I cant do
my work, because some computer that Ive never
even heard of, has failed (Leslie
Lamport)
3
Distributed Systems

• Network of processes communicating with one
  another
• to meet some objective.
• Growth and innovations fueled by
• Declining hardware cost and improved device
  functionality
• Better networking facility
• Our dreams

4
Distributed Systems

• Traditional Client server systems
• Peer to peer networks
• Communicating micro-robots
• Sensor networks
• Vehicular networks

5
A client-server system
S
server
clients
(boring )
6
Communicating micro-robots
Courtesy the iSwarm project at the University of
Karlsruhe
7
Numerous Challenges

• Processes have local views, but the goals are
  global.
• Failures and perturbations are expected events
  and not catastrophic exceptions!
• Clocks are not perfectly synchronized
• The topology may change from time to time

8
Replicated servers
not so easy
clients
S1
S
S2
S0
server
S3
Client-server
Replicated client-server
9
Vehicular Networks

• Applications
• Accident alerts/prevention
• Dynamic route planning
• Entertainment

• Communications
• Cellular network
• Vehicle to roadside
• Vehicle to vehicle

10
Topics to explore

• Designing fault-tolerant distributed systems
• (The term fault has a wide scope. It does not
  necessarily mean crash, but include selfishness,
  malicious behavior, node mobility, environmental
  changes etc)

11
Topics to explore

• To prevent disruptions caused by failures and
  perturbations,
• distributed systems must learn to manage
  themselves without
• external intervention (which is often costly, and
  sometimes not
• practical). This means, most non-trivial
  distributed systems must
• satisfy one or more of the following properties
• self-organization, self-healing,
  self-stabilization, self-optimization etc.
• (These are yardsticks of smartness)

12
Topics to explore

• Scalable algorithms for distributed systems.
  Some large scale systems have millions of nodes
  in them. Will your solution be practical at that
  scale?
• Dealing with big data in distributed systems
• (cloud computing, MapReduce, Hadoop etc)

13
Topics to explore

• The goal is to guarantee that the system will
  work in real life. If it does not, then you have
  to question and revisit the model assumptions,
  algorithm correctness etc.

practice
theory
14
Graduate courses

• If you are interested in such topics, then
  consider taking
• (Fall 2012)
• 22C166 Distributed Systems and Algorithms
  (Sukumar Ghosh)
• 22C 196 Sensing the world (Octav Chipara)
• (Other semesters)
• 22C196 Parallel and Distributed Programming
  Forms and Limits
• Cloud Computing (Ted Herman)
• Sensor Networks (Ted Herman)
• Advanced Distributed Algorithms (Sriram
  Pemmaraju)